Fouling is an inevitable problem faced in industries where material is in contact with free flowing or stagnant liquids. Main consequence of fouling is decreased thermal efficiency and an increased pressure drop in heat exchangers. Consequently, fouling results in catastrophic failures and increased operational and maintenance costs in the industries. Lots of research has been carried out to understand the mechanism of fouling and its mitigation. But reported research has been lacking in developing predictive tools. The work undertaken in this research, focusses on the development of a predictive model for fouling in artificial sea water in the presence of starch. Starch is reported to be a very good corrosion inhibitor. By all probabilities, it is expected to reduce corrosion fouling. From Response Surface Methodology (RMS), Box Behnken design has been adopted for the experimental design. Fouling propensity is expressed in terms of mass gain. Fouling is a time dependent process and therefore time has been chosen as an important parameter for study. Other parameters include flowrate and temperature. The best operating conditions with least fouling propensity was found to be 60°C, 12 liters per minutes and 6.00 h time duration.